Job Description Summary
The Sr Staff Enterprise AI Architect will lead the design, standardization, and scaling of enterprise-grade AI solutions across strategic business initiatives. This role will define reusable AI architecture patterns, guide implementation teams on modern AI/GenAI approaches, and ensure alignment with enterprise standards for scalability, security, reliability, observability, and cost optimization.
The ideal candidate brings deep expertise in Generative AI solution architecture, Retrieval-Augmented Generation (RAG), agentic AI systems, LLM orchestration, enterprise data integration, and AI platform engineering. This individual will work closely with business, product, data, and engineering teams to accelerate the adoption of reusable AI capabilities and production-ready AI solutions across the enterprise.
Job Description
Roles & Responsibilities
Define and drive enterprise AI architecture strategy across multiple business domains and AI initiatives.
Architect scalable, reusable, and secure AI/GenAI solution patterns for enterprise adoption.
Lead solution design for Generative AI/ Physical AI/ Vision AI applications including RAG pipelines, agentic workflows, AI copilots, document intelligence, and enterprise search.
Establish enterprise standards for:
Model selection and orchestration
Prompt engineering and prompt management
Chunking and embedding strategies
Hybrid retrieval approaches
Vector database integration
Agentic orchestration frameworks
AI observability, evaluation, and monitoring
Guide teams on advanced retrieval architectures, semantic search, non-sequential document understanding, and contextual information extraction.
Design reusable AI services and accelerators that can be leveraged across multiple use cases and business units.
Collaborate with enterprise platform, cloud, data, and cybersecurity teams to ensure AI solutions align with enterprise architecture and governance standards.
Standardize integration patterns with enterprise systems including data lakes, ERP systems, workflow platforms, and operational applications.
Drive architectural decisions balancing scalability, maintainability, performance, security, and cost efficiency.
Define enterprise AI evaluation frameworks covering accuracy, hallucination tracking, latency, reliability, and operational KPIs.
Influence AI platform roadmap and foundational AI services by providing architectural guidance and identifying capability gaps.
Conduct architecture reviews and provide technical leadership for critical AI programs and production deployments.
Partner with engineering and product teams to accelerate AI solution delivery through reusable frameworks and best practices.
Mentor and upskill engineering teams on enterprise AI architecture patterns, GenAI best practices, and emerging AI technologies.
Stay current with evolving AI ecosystem trends, frameworks, foundation models, and enterprise AI architectural practices.
Educational Qualification
Bachelor’s degree in Computer Science, Information Technology, Engineering, or related technical discipline from an accredited institution.
Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field is preferred.
Desired Characteristics
12+ years of experience in
enterprise software architecture
, platform engineering, or digital technology leadership roles.
5+ years of experience in
AI/ML solution architecture
with strong focus on enterprise AI and Generative AI systems.
Strong expertise in:
Generative AI
and
LLM-based solution architecture
Retrieval-Augmented Generation (
RAG
)
Agentic AI frameworks
and orchestration
Prompt engineering
and evaluation techniques
Vector databases
and
semantic retrieval systems
AI observability and evaluation frameworks
Experience designing
enterprise-scale AI platforms
on major cloud providers such as
Amazon Web Services / Microsoft Azure
Strong understanding of
enterprise data architecture
, APIs, integration patterns, and distributed systems.
Experience integrating AI solutions with enterprise platforms such as Databricks, ERP systems, document repositories, and operational systems.
Familiarity with modern AI/ML frameworks and orchestration technologies such as
LangChain
,
LangGraph
,
Semantic Kernel
, or equivalent frameworks.
Strong understanding of
AI governance, security, responsible AI,
and enterprise compliance considerations.
Demonstrated ability to influence technical strategy and drive alignment across cross-functional engineering and business teams.
Excellent communication, stakeholder management, and executive presentation skills.
Ability to operate effectively in fast-paced, highly collaborative, and ambiguous environments.
Strong problem-solving mindset with the ability to balance innovation with pragmatic enterprise delivery considerations.
Additional Information
Relocation Assistance Provided:
Yes
